Data Analyst

Overview

Zig by ComfortDelGro seeks a Data Analyst dedicated to transforming complex datasets into actionable insights through compelling dashboards and meticulous reporting. This role involves close collaboration with product, operations, and business teams to convert questions and challenges into informed, data-driven decisions.

Key Responsibilities

• Create and sustain interactive dashboards and reports leveraging tools like Power BI, Tableau, or Looker to aid business monitoring and strategic choices.
• Conduct in-depth data analysis to detect trends, irregularities, and root causes across critical business metrics.
• Partner with stakeholders to shape business inquiries into clear analytical problems, establish success indicators, and design measurement models.
• Use proficient SQL skills to extract and transform data from warehouses or data lakes, preparing it for detailed analysis and reporting.
• Ensure data integrity by troubleshooting quality issues and working alongside data engineers to enhance pipelines and definitions.
• Communicate analytical discoveries and recommendations effectively through visuals, documentation, and presentations suitable for both technical and non-technical audiences.
• Help develop and maintain standardized metrics, business definitions, and reporting protocols.
• Initiate improvements on dashboards, automate routine reports, and refine analytical tools and frameworks.
• Fulfill additional relevant tasks as assigned.

Qualifications

• Bachelor’s degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or Business Analytics.
• Preferably 1 to 3 years of relevant experience as a Data Analyst, Data Scientist, Business Analyst, or comparable analytic position.
• Strong knowledge of at least one BI/dashboard platform including data modelling, visualization design, and optimization.
• Expertise in SQL with experience handling large-scale data from relational databases, data warehouses, or lakes.
• Competency in Python or R for data analysis using libraries like Pandas and NumPy is highly advantageous.
• Sound grasp of data modelling principles, joins, aggregations, and quality control.
• Experience performing comprehensive data dives to answer business questions, assess impacts, and diagnose issues.
• Familiarity with statistical testing methods, A/B testing, and experimentation is beneficial.
• Experience in sectors such as ride-hailing, logistics, or e-commerce is a plus.
• Strong business acumen to link data insights to practical product or operational outcomes.
• Excellent analytical problem-solving skills with a methodical strategy for complex issues and assumptions validation.
• Attention to detail with a commitment to ensuring data precision and reliability.
• Effective in communicating complex analytics and findings to varied audience types.